Critical RGC-Expected Survival models for predicting Survival of planted white fir (Abies concolor Lindl.) seedlings
Authors: Stone, E.C.; Cavallaro, J.I.; Norberg, E.A.
Source: New Forests, Volume 26, Number 1, July 2003 , pp. 65-82(18)
Heretofore, only regression models using average RGC as the independent variable were available to predict the survival of planted seedlings. Now, however, Critical RGC-Expected Survival models are available. Each model predicts the survival of a population on sites with the same Critical RGC as specified by the model. Survival is predicted to equal the percent of the seedlings in the population that have RGCs≥ that Critical RGC. These models are validated by a chi-square goodness of fit test which determines the probability that the survival predictions made by a model agree with the survivals observed on a planting site. In validating a model, the harshness of the planting site is also quantified in terms of its Critical RGC. In this paper, three Critical RGC-Expected Survival models are validated, demonstrating that RGC controls survival on both harsh and gentle sites. On the harsher sites, the Critical RGC for survival was 40 cm; whereas on the gentler sites, it was 20 cm.
Document Type: Research Article
Affiliations: Department of Environmental Science, Policy, and Management, University of California, 145 Mulford Hall, Berkeley, 94720, USA
Publication date: July 1, 2003